Literatura académica sobre el tema "BOX-JENKINS"
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Artículos de revistas sobre el tema "BOX-JENKINS"
Kremer, Erhard. "Box-Jenkins credibility". Blätter der DGVFM 18, n.º 4 (octubre de 1988): 277–89. http://dx.doi.org/10.1007/bf02808821.
Texto completoPepper, M. P. G. "Multivariate Box-Jenkins analysis". Energy Economics 7, n.º 3 (julio de 1985): 168–78. http://dx.doi.org/10.1016/0140-9883(85)90006-4.
Texto completoPintelon, R., J. Schoukens y Y. Rolain. "Box-Jenkins Continuous-Time Modeling". IFAC Proceedings Volumes 33, n.º 15 (junio de 2000): 193–98. http://dx.doi.org/10.1016/s1474-6670(17)39749-5.
Texto completoLu, Y. y S. M. AbouRizk. "Automated Box–Jenkins forecasting modelling". Automation in Construction 18, n.º 5 (agosto de 2009): 547–58. http://dx.doi.org/10.1016/j.autcon.2008.11.007.
Texto completoPintelon, R., J. Schoukens y Y. Rolain. "Box–Jenkins continuous-time modeling". Automatica 36, n.º 7 (julio de 2000): 983–91. http://dx.doi.org/10.1016/s0005-1098(00)00002-9.
Texto completoKhalfi, Jaouad, Najib Boumaaz, Abdallah Soulmani y El Mehdi Laadissi. "Box–Jenkins Black-Box Modeling of a Lithium-Ion Battery Cell Based on Automotive Drive Cycle Data". World Electric Vehicle Journal 12, n.º 3 (28 de julio de 2021): 102. http://dx.doi.org/10.3390/wevj12030102.
Texto completoHelfenstein, Ulrich. "Box-Jenkins modelling in medical research". Statistical Methods in Medical Research 5, n.º 1 (marzo de 1996): 3–22. http://dx.doi.org/10.1177/096228029600500102.
Texto completoPintelon, R., P. Guillaume y J. Schoukens. "MULTIVARIABLE FREQUENCY DOMAIN BOX-JENKINS IDENTIFICATION". IFAC Proceedings Volumes 39, n.º 1 (2006): 208–13. http://dx.doi.org/10.3182/20060329-3-au-2901.00027.
Texto completoPiga, Dario, Valentina Breschi y Alberto Bemporad. "Estimation of jump Box–Jenkins models". Automatica 120 (octubre de 2020): 109126. http://dx.doi.org/10.1016/j.automatica.2020.109126.
Texto completoPintelon, R., J. Schoukens y P. Guillaume. "Box–Jenkins identification revisited—Part III". Automatica 43, n.º 5 (mayo de 2007): 868–75. http://dx.doi.org/10.1016/j.automatica.2006.11.007.
Texto completoTesis sobre el tema "BOX-JENKINS"
Businger, Mark P. "Suitability of Box-Jenkins modeling for Navy repair parts". Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1996. http://handle.dtic.mil/100.2/ADA319073.
Texto completoBiondi, Franco y Thomas W. Swetnam. "Box-Jenkins Models of Forest Interior Tree-Ring Chronologies". Tree-Ring Society, 1987. http://hdl.handle.net/10150/261796.
Texto completoGustavsson, André. "Prognossäkerhet : Tillför en heteroskedastisk modell någon säkerhet hos Box och Jenkins prognosmodeller?" Thesis, Umeå University, Department of Statistics, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-34825.
Texto completoDrevna, Michael J. "An application of Box-Jenkins transfer functions to natural gas demand forecasting". Ohio : Ohio University, 1985. http://www.ohiolink.edu/etd/view.cgi?ohiou1183999594.
Texto completoRIBEIRO, LUIZ CLAUDIO. "IDENTIFICATION OF BOX AND JENKINS: A COPARISON BETWEEN FACE AND PADÉ APPROXIMATION". PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 1992. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=9016@1.
Texto completoSince 1970, when Box and Jenkins first introduced the ARMA models to analysis and predict of time series data, a lot of studies have been developed to find an efficient identification method for such models. This was due the fact that the identification method proposed by Box and Jenkins, based on Auto-correlation Function (ACF) and Partial Auto-correlation Function (PACF), are inefficient when the models have auto regressive - AR- and moving average - MA- components. Comparative studies undertaken, have shown that, among the identification methods already developed, the method based on the Extended Auto-correlation Fuction of Tiao and Tsay (1982) is the most efficient. More recently, however, Kuldeep Kumar has introduced in the literature an identification method based on the theory of Padé aproximation. The objective of this paper is to compare the Extended Auto-correlation Function method with the method based on the Theory of Padé approximation.
Queirós, Emerson Oliveira de. "Modelo de previsão para receita tributária estadual: aplicação da metodologia Box-Jenkins". Pontifícia Universidade Católica de São Paulo, 2012. https://tede2.pucsp.br/handle/handle/9196.
Texto completoCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
The goal of the present work it to use the Box-Jenkins methodology, also known as ARIMA methodology, to build a short-term model of prediction for the state tax (ICMS) revenue. This tax is the most important source of income for the states in Brazil. Therefore, to predict precisely the volume of resources to be collected, other then being a legal requirement, may also be crucial for the financial management of the States. The results achieved indicate that the Box-Jenkins methodology can be a useful tool to forecast the short-term tax revenue from taxes with the characteristics of the ICMS (Value Add Tax)
O presente trabalho objetiva aplicar a metodologia Box-Jenkins, conhecida também como metodologia ARIMA, a fim de construir um modelo de previsão de curto prazo para o imposto estadual (ICMS). Trata-se de um imposto de grande peso relativo nas receitas dos estados no Brasil. Portanto, antecipar precisamente o volume de recursos advindos da principal fonte de receita dos estados no Brasil, além de ser uma imposição legal, pode ser também crucial na gestão financeira dos Estados. Os resultados indicaram que a metodologia Box-Jenkins pode ser uma ferramenta útil se a intenção for construir um modelo de previsão de curto prazo para o imposto com as características do ICMS
BALTAR, BRUNO DE PAULA. "TEMPORAL ANALYSIS OF COMMODITY COPPER PRICES´S USING THE BOX & JENKINS MODEL". PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2009. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=13919@1.
Texto completoThis paper studies the behavior of copper prices following the Box & Jenkins model. The dissertation aims to test the validity of this model in explaining the behavior of this commodity. Copper presents one of the most liquid contract among commodities which may increase the information within its price dynamics. This paper is structured as follows: the first section presents a brief historic evolution of copper prices; the second presents relevant previous papers on this matter; the third presents a deep description of the model used and; the fourth, the conclusion. The data set comprises 19 years of daily prices, between 1990 and 2008. Tests for normality, estacionarity and auto-correlation had been carried through, identifying the best models to be used. The paper concludes that past copper price returns partially explain the series future behavior. However, short term forecasting based only on this variable posts just modest performance.
PINTO, RODRIGO BASTOS. "BEHAVIORAL FINANCE AND BOX AND JENKINS METHODOLOGY: AN APPLICATION ON THE BRAZILIAN MARKET". PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2006. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=8764@1.
Texto completoEsta dissertação aborda um tema bastante recente e ainda controverso, intitulado Finanças Comportamentais. O estudo se inicia com a apresentação de alguns dos conceitos e estudos já realizados nesta área, onde estão inseridas algumas críticas à hipótese de mercado eficiente e à idéia de caminho aleatório. Estas críticas levam a outros três conceitos, conhecidos como auto-correlação entre os retornos, reversão a média e previsibilidade do retorno de ativos, que são, na verdade, o interesse central do trabalho. Para explorar estes três conceitos será aplicada a metodologia de Box&Jenkins sobre as séries de retornos diários das 50 ações mais líquidas listadas na BOVESPA, sendo que o período analisado vai de 01/01/1994 até 31/12/2005. Ao final, conclui-se que existem evidências de autocorrelação entre os retornos diários das ações, que existe uma possível indicação de que os retornos oscilam em torno de uma média e de que o modelo de previsão baseado em resultados passados tem performance, apenas, razoável.
This dissertation approaches a very recent and controversial issue named Behavioral Finance. So, this work begins presenting some of the concepts and studies carried out in the area, where some criticism of the efficient market hypothesis and the random walk idea is made. This criticism drives to another three concepts: autocorrelation of asset return, mean reversion and predictability of asset return, which, indeed, are the central issues of this work. To explore these three concepts the Box&Jenkins model will be applied on daily return time series of the most 50 liquid stocks listed in the São Paulo Stock Exchange (BOVESPA), between 01/011994 thru 12/31/2005. At the end, the study concludes that exist autocorrelation evidences among daily returns, that there is a possible indication of mean reversion, and that the forecast model based on past results has just a regular performance.
Thibodeau, Katlyn. "Application de la méthodologie Box-Jenkins aux séries du Ministère de la Santé". Thèse, Université du Québec à Trois-Rivières, 2011. http://depot-e.uqtr.ca/2710/1/030290608.pdf.
Texto completoClaudio, Cordeiro Teti Aloisio. "Modelo de previsão da receita tributária : o caso do ICMS no Estado de Pernambuco". Universidade Federal de Pernambuco, 2009. https://repositorio.ufpe.br/handle/123456789/3786.
Texto completoEsta dissertação tem como principal objetivo apresentar os modelos de previsão de arrecadação do ICMS, por segmento econômico, para a Secretaria da Fazenda do Estado de Pernambuco, utilizando as técnicas econométricas. Objetiva-se, com essa pesquisa, disponibilizar aos gestores púbicos do Estado mais um modelo de previsão consistente e com certo grau de confiabilidade. Para tanto, utilizou-se da metodologia Box-Jenkins, mais especificamente os modelos: ARIMA - modelo autorregressivo integrado de média móvel, e SARIMA - modelo autorregressivo integrado de média móvel sazonal, e o software RATS (Regression Analyse Time Series). O trabalho apresenta o comportamento da arrecadação de ICMS no Estado e uma revisão da literatura, onde são abordados os principais conceitos teóricos utilizados, bem como uma análise dos resultados obtidos. Conclui-se que o modelo de previsão utilizando séries temporais, em função de sua capacidade preditiva, pode se transformar em um valioso instrumento para auxiliar na elevação da receita tributária no Estado de Pernambuco, dentro da capacidade contributiva de cada contribuinte
Libros sobre el tema "BOX-JENKINS"
Evaluation mit Hilfe der Box-Jenkins-Methode: Eine Untersuchung zur Überprüfung der Wirksamkeit einer legislativen Massnahme zur Erhöhung der richterlichen Arbeitseffektivität im Bereich der Zivilgerichtsbarkeit. Frankfurt am Main: P. Lang, 1986.
Buscar texto completoGeōrganta, Zōē. Hē prosengisē Box-Jenkins stēn analysē kai provlepsē chronologikōn seirōn. Athēna: Kentro Programmatismou kai Oikonomikōn Ereunōn, 1987.
Buscar texto completoAbou-El-Fetouh, Mohamed Fathi. Forecasting the number of external pilgrims: A Box-Jenkins approach. [Riyadh, Saudi Arabia]: King Saud University, College of Administrative Sciences, Research Center, 1987.
Buscar texto completoBedoya, Manuel Otarola. El ciclo cuantitativo: Una aplicación metodológica no estacionaria para el corto plazo en el caso peruano, período 1989-1992. Lima, Perú: Facultad de Economía, Universidad de Lima, 1993.
Buscar texto completoLöderbusch, Bernhard. Modelle zur Aktienkursprognose auf der Basis der Box/Jenkins-Verfahren: Eine empirische Untersuchung. Krefeld: G. Marchal und H.-J. Matzenbacher Wissenschaftsverlag, 1985.
Buscar texto completoWerner, Fuchs. Box-Jenkins-Prognosen der kurzfristigen Produktionsentwicklung: Dargestellt am Beispiel ausgewählter Branchen des verarbeitenden Gewerbes in der Bundesrepublik Deutschland zwischen 1976 und 1985. Bergisch Gladbach: J. Eul, 1989.
Buscar texto completoBabeshko, Lyudmila y Irina Orlova. Econometrics and econometric modeling in Excel and R. ru: INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1079837.
Texto completoSuitability of Box-Jenkins Modeling for Navy Repair Parts. Storming Media, 1996.
Buscar texto completoPankratz, Alan. Forecasting with Univariate Box - Jenkins Models: Concepts and Cases. Wiley & Sons, Incorporated, John, 2009.
Buscar texto completoZappe. Forecasting with Univariate Box-Jenkins Models: Co Ncepts and Cases, Second Edition. John Wiley & Sons Inc, 2008.
Buscar texto completoCapítulos de libros sobre el tema "BOX-JENKINS"
Cipra, Tomas. "Box–Jenkins Methodology". En Time Series in Economics and Finance, 123–73. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-46347-2_6.
Texto completoTunnicliffe Wilson, Granville y Peter Armitage. "Box-Jenkins Seasonal Models". En System Identification, Environmental Modelling, and Control System Design, 153–70. London: Springer London, 2012. http://dx.doi.org/10.1007/978-0-85729-974-1_8.
Texto completoAljandali, Abdulkader. "The Box-Jenkins Methodology". En Multivariate Methods and Forecasting with IBM® SPSS® Statistics, 59–79. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56481-4_3.
Texto completoBoland, John. "Box–Jenkins Time Series Models". En International Encyclopedia of Statistical Science, 178–81. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-04898-2_153.
Texto completoMills, Terence C. "Box and Jenkins: Developments Post-1970". En A Very British Affair, 240–87. London: Palgrave Macmillan UK, 2013. http://dx.doi.org/10.1057/9781137291264_8.
Texto completoSchlittgen, Rainer. "Box-Jenkins Prognosen mit Fehlerhaften Modellen". En Operations Research Proceedings, 490–97. Berlin, Heidelberg: Springer Berlin Heidelberg, 1985. http://dx.doi.org/10.1007/978-3-642-70457-4_125.
Texto completoAsteriou, Dimitrios y Stephen G. Hall. "ARIMA Models and the Box-Jenkins Methodology". En Applied Econometrics, 275–96. London: Macmillan Education UK, 2016. http://dx.doi.org/10.1057/978-1-137-41547-9_13.
Texto completoXie, Li, Huizhong Yang y Feng Ding. "Interactive Identification Method for Box-Jenkins Models". En Communications in Computer and Information Science, 163–69. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15859-9_23.
Texto completoStahl, Herbert, Mikael Weigelt y Götz Wiegand. "Box-Jenkins Analysis of Air Pollution Data". En Operations Research Proceedings, 417–24. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-73778-7_107.
Texto completoLaurain, Vincent, Marion Gilson y Hugues Garnier. "Refined Instrumental Variable Methods for Hammerstein Box-Jenkins Models". En System Identification, Environmental Modelling, and Control System Design, 27–47. London: Springer London, 2012. http://dx.doi.org/10.1007/978-0-85729-974-1_2.
Texto completoActas de conferencias sobre el tema "BOX-JENKINS"
Darwish, Mohamed, Pepijn Cox, Gianluigi Pillonetto y Roland Toth. "Bayesian identification of LPV Box-Jenkins models". En 2015 54th IEEE Conference on Decision and Control (CDC). IEEE, 2015. http://dx.doi.org/10.1109/cdc.2015.7402087.
Texto completoLi, Gong y Jing Shi. "Comparison of Different Time Series Methods for Short-Term Forecasting of Wind Power Production". En ASME 2010 4th International Conference on Energy Sustainability. ASMEDC, 2010. http://dx.doi.org/10.1115/es2010-90270.
Texto completoBreschi, Valentina, Dario Piga y Alberto Bemporad. "Maximum-a-posteriori estimation of jump Box-Jenkins models". En 2019 IEEE 58th Conference on Decision and Control (CDC). IEEE, 2019. http://dx.doi.org/10.1109/cdc40024.2019.9030097.
Texto completoGhomi, S. M. T. Fatemi y K. Forghani. "Airline passenger forecasting using neural networks and Box-Jenkins". En 2016 12th International Conference on Industrial Engineering (ICIE). IEEE, 2016. http://dx.doi.org/10.1109/induseng.2016.7519342.
Texto completoSchoukens, J., Y. Rolain, G. Vandersteen y R. Pintelon. "User friendly Box-Jenkins identification using nonparametric noise models". En 2011 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC 2011). IEEE, 2011. http://dx.doi.org/10.1109/cdc.2011.6160204.
Texto completoVictor, Ste´phane, Rachid Malti y Alain Oustaloup. "Instrumental Variable Method for Identifying Fractional Box-Jenkins Models". En ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/detc2009-86984.
Texto completoHu, Xinyao, Shicong Meng, Cong Shi, Dingyi Han y Yong Yu. "Predicting Query Duplication with Box-Jenkins Models and Its Applications". En Seventh IEEE International Conference on Peer-to-Peer Computing (P2P 2007). IEEE, 2007. http://dx.doi.org/10.1109/p2p.2007.21.
Texto completoHu, Xinyao, Shicong Meng, Cong Shi, Dingyi Han y Yong Yu. "Predicting Query Duplication with Box-Jenkins Models and Its Applications". En Seventh IEEE International Conference on Peer-to-Peer Computing (P2P 2007). IEEE, 2007. http://dx.doi.org/10.1109/p2p.2007.4343467.
Texto completoĐukec, Damira. "FORECASTING TOURISM DEMAND IN CROATIA USING BOX AND JENKINS METHODOLOGY". En Tourism in Southern and Eastern Europe: Creating Innovative Tourism Experiences: The Way to Extend the Tourist Season. University of Rijeka, Faculty of Tourism and Hospitality Management, 2019. http://dx.doi.org/10.20867/tosee.05.18.
Texto completoIsmail, Zuhaimy, Mohd Zulariffin Md Maarof y Mohammad Fadzli. "Alteration of Box-Jenkins methodology by implementing genetic algorithm method". En THE 2ND ISM INTERNATIONAL STATISTICAL CONFERENCE 2014 (ISM-II): Empowering the Applications of Statistical and Mathematical Sciences. AIP Publishing LLC, 2015. http://dx.doi.org/10.1063/1.4907522.
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